I don't see this that would make it snowflake more like what I think as conforming dimensions. You need to make sure the grain of the measures is at what level , the they are same grain then you should be good however if they are different then you would start seeing null values.

Fact Measures use the same, conformed dimensions like Dim1 and Dim a if you trying to generate from multiple facts, the BI server was able to automatically stitch them together into a single result set. If they came from the same fact table that's easy as its only one single table, but if you are pulling from different fact tables, the conformed dimensions would allow them to be stitched into the same report

Conformance means that these sources can be mapped to a common structure – the same levels – and also the same data members.

Is it necessary to add dim a as an LTS in Dim1? I already have Dim 1 present as a simnsion table in my BMM layer...would it work fine if I just join dim1 and dim a in Physical layer and not define lts?

Is it necessary to add dim a as an LTS in Dim1? I already have Dim 1 present as a simnsion table in my BMM layer...would it work fine if I just join dim1 and dim a in Physical layer and not define lts?

I actually have to join both dim1 and dim2(part of f1) to dim a(part of f2).

dim1,2,a are present as seperate dimension tables in my BMM layers.I have defined both the joins in Physical layer.now, to maintain star schema, I just need to add dima as an LTS in either dim1 or dim2?Do I need to make any other changes in BMM as well?

My report selects data from F1,D1,D2,D3,DA only...doesn't involve F2 at all....now as per the join conditions D1,D2,D3 join to F1 and DA joins to D1,D2.So all the tables are now joined to fetch correct data.Also, I have defined DA as an LTS in D1 in BMM.I guess no need to add DA in LTS for D2 now?